Redbird AI automates the data flow between your lakehouse and enterprise database. Stop manually exporting transformed data, building brittle ETL scripts, or waiting on data engineering for every SQL Server sync—let AI handle schema mapping, incremental loads, and bi-directional pipelines.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically push cleaned, transformed data from Delta Lake to SQL Server tables as your pipeline completes. Redbird handles schema drift, upserts based on primary keys, and incremental syncs so your Power BI dashboards and enterprise apps always have fresh lakehouse data.
Pull order, customer, and inventory records from SQL Server into Delta Lake on a schedule or trigger. Redbird orchestrates incremental extraction, type conversion, and partitioning so your ML pipelines always train on the latest operational data without manual JDBC configuration.
After scoring in Databricks, write predictions—churn probability, recommendation IDs, forecast values—directly to SQL Server tables used by CRM and ERP systems. Redbird maps model output schemas to target tables and handles batch or streaming writes automatically.
Migrate aged transactional records from SQL Server to Delta Lake based on date thresholds or table size. Redbird compresses, partitions, and catalogs archived data in your lakehouse while maintaining queryability and reducing SQL Server storage costs.
Take engineered features—lifetime value scores, behavior segments, aggregated metrics—from your Databricks feature store and write them back to SQL Server customer tables. Your applications and stored procedures instantly access advanced analytics without custom integration code.
Monitor SQL Server schema changes—new columns, altered types, dropped indexes—and trigger notifications or pipeline adjustments in Databricks. Redbird detects drift before it breaks your ETL jobs and suggests schema evolution strategies for Delta tables.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and SQL Server with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands both Databricks Delta Lake schemas and SQL Server relational structures—automatically mapping between lakehouse tables and normalized enterprise databases without custom connectors.
Redbird reads your Databricks table metadata, partition schemes, and data types alongside SQL Server schemas, constraints, and indexes. It suggests optimal sync strategies—full refresh vs. merge, columnstore indexing, partition pruning—based on table size and update patterns. When schemas evolve in either system, Redbird detects changes and adjusts mappings automatically, handling type coercion between Spark SQL and T-SQL data types without breaking pipelines.
faster than building custom JDBC pipelines between Databricks and SQL Server
Redbird can pull from Databricks and SQL Server simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Databricks or SQL Server.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Databricks into SQL Server, or from SQL Server back into Databricks. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from any Databricks job completion or SQL Server table change—Redbird orchestrates the rest across both platforms.
Fires when new data is written to a Delta Lake table via pipeline or streaming job.
Triggers when a scheduled notebook, ETL pipeline, or ML training job finishes successfully.
Fires when a new model version is logged to the Databricks MLflow registry.
Insert or merge records into a Delta Lake table with automatic schema evolution.
Execute a specific notebook with parameters for ad-hoc processing or analysis.
Start a multi-task job orchestration for complex ETL or ML pipelines.
Fires when rows are inserted, updated, or deleted in a monitored SQL Server table.
Triggers after a specific SQL Server stored procedure executes successfully.
Fires when table structure, indexes, or constraints are modified in SQL Server.
Write new rows to a target table with batch optimization and error handling.
Merge records into SQL Server using key matching—update existing, insert new.
Run custom T-SQL statements or call stored procedures with dynamic parameters.
Join teams that sync Databricks and SQL Server automatically. Stop writing JDBC boilerplate and let Redbird handle the data flow between your lakehouse and enterprise database.